Rank aggregation is the issue of producing an `Icon sensus" ranking for a given arrangement of rankings. At the point when connected to the web, this discovers applications in meta-searching, spam fighting and word association methods. Rank aggregation can be thought of as the unsupervised analog to regression, in which the objective is to locate an aggregate ranking that limits the separation to every one of the positioned records in the info set. Rank aggregation has likewise been proposed as an effective method for closest neighbor positioning of categorical data, and gives a robust way to deal with the issue of consolidating the conclusion of specialists with various scoring schemes, as are basic in ensemble methods. In ranking aggregation, the objective is to outline a gathering of rankings over an arrangement of choices by a single (consensus) positioning. This issue has been the subject of a good arrangement of consideration in different fields: beginning from races in elections decision hypothesis.

Rank Aggregation, Particle Swarm Optimization, Genetic Algorithm, Robust Rank Aggregation

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